Microsoft Releases Batch Shipyard on GitHub for Docker on Azure

Microsoft continues to augment it’s Azure cloud for HPC workloads with the release of the Batch Shipyard toolkit, version 1.0.

Available on GitHub as Open Source, the Batch Shipyard toolkit enables easy deployment of batch-style Dockerized workloads to Azure Batch compute pools. Azure Batch enables you to run parallel jobs in the cloud without having to manage the infrastructure. It’s ideal for parametric sweeps, Deep Learning training with NVIDIA GPUs, and simulations using MPI and InfiniBand. Whether you need to run your containerized jobs on a single machine or hundreds or even thousands of machines, Batch Shipyard blends features of Azure Batch — handling complexities of large scale VM deployment and management, high throughput, highly available job scheduling, and auto-scaling to pay only for what you use — with the power of Docker containers for application packaging. Batch Shipyard allows you to harness the deployment consistency and isolation for your batch-style and HPC containerized workloads, and run them at any scale without the need to develop directly to the Azure Batch SDK.

The initial release of Batch Shipyard has the following major features:

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